Data-driven VC: January Roundup
Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Tuesday, I publish “Insights” to digest the most relevant startup research & reports, and every Thursday, I publish “Essays” that cover hands-on insights about data-driven innovation & AI in VC. Follow along to understand how startup investing becomes more data-driven, why it matters, and what it means for you.
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Welcome to our monthly wrap-up episode where we’ll cover January’s most relevant content at the intersection of VC, startups, data, AI & productivity. I read it all so you don’t need to - here we go👇
INTERESTING RESEARCH & REPORTS📈
This section is a teaser for what you can expect from our new weekly “Insights” episodes launching next Tuesday: Alternating formats that “Digest” the most interesting startup research & reports from the previous two weeks + “Synthesize” all available research to create a deep knowledge base for various startup topics.
What are the patterns of successful startups? We ran the numbers on 25k+ teams and found:
Number of executives: 3-6 is best, single founder is worst
CEO: Important to be founder, external CEO is bad
Age: Teams with higher age are more successful; little difference between 25 to early 40s
Education: Master and PhD similarly good, Bachelors and no degree both bad
Equity for Advisors: What's the Benchmark? When it comes to equity grants for advisors in US startups, recent Carta data from 47k+ advisor grants reveals some intriguing benchmarks:
Pre-Seed: Typically advisors receive a median grant of 0.25% of the company, aligning with the value suggested in the FAST templates
Seed Stage: Advisors at this stage see a median grant of 0.1%, marking a noticeable drop from 2022
Series A: The median grant stabilizes at 0.07%, remaining flat compared to the previous two years
INSPIRING TECH IN VC CONTENT💡
“How Venture Capitalists Are Using AI To Invest More Effectively” article by Vital Laptenok via Entrepreneur here, exploring how AI can augment or even replace human investors across the following tasks
Sourcing and screening startups
Monitoring startups with high potential
“AI Tools for VC” list by VC Lab here, highlighting useful tools across general research, thesis building, deal flow management, meetings, back office, and fundraising & LP investor relations
“Venture Capital's New Era: AI's Journey From Enhancing Operational Efficiency To Alpha Generation” by Josipa Majic Predin in Forbes here, sharing how firms like Sequoia, A16Z, Tiger Capital, Iconiq, and others are using AI tools for two primary goals:
Anything from data analysis to co-pilot options to improve their daily operational efficiency e.g. document generation and process management using generative AI technology
Generating alpha includes more complicated tasks that require predictive AI: from sourcing deals to invest in, matching with optimal LPs that could invest in their fund to recruiting the best candidates to hire for existing portfolio companies
Reddit and Seven Seven Six Co-Founder Alexis Ohanian joined Erik Torenberg in the Turpentine VC podcast here to discuss how his firm is a “tech company that deploys venture capital”, the lack of internal metrics in venture, and how he plans to reinvent venture using software
Rob Kniaz from H Tree Capital and Hoxton Ventures joined Ernests Stals in the Starwatcher Podcast here, talking about the changing investment landscape, how that is affected by the availability of data, and diving into some technical aspects of LLM's, data scraping, and data analysis for investors
“Data-driven VC Landscape 2023” report explores how leading investors leverage data & AI by shedding light on 151 top VCs, 65 thought leaders, 400+ tools, hands-on guides for integrating ChatGPT, LLMs, and a lot more - participate in the next edition below👇
I’m planning a virtual “Data-driven VC Summit”. Sign up here if you’d like to join for free
“Catalyzing Change: The Power of AI & Data Science in Revolutionizing VC Fund Dynamics” panel with Ties Boukema (Dawn Capital), Konstantin Vinogradov (Runa Capital), Jack Leeney (7GC) , Marek Zamecnik (Vestberry), and myself at the 0100 Conference Feb 29, 2024 in Vienna here
“TECH IN VC” JOBS👩💻
🔥Senior Software Engineer @Earlybird VC in Munich or Berlin here🔥
🔥Software Engineer Intern @Earlybird VC in Munich or Berlin here🔥
Tech Lead @All Iron Ventures in Bilbao here
Product Analyst @Balderton based in London here
Data Scientist @Blossom in London here
Analytics Engineer @Dawn Capital in London here
ML master student @EQT in Stockholm here
Data Engineer @Ethereal Ventures remote here
Analytics Engineer @Tidemark Capital in San Francisco Bay Area here
THIS MONTH’S DATA-DRIVEN VC EPISODES⏮️
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If you have any suggestions, want me to feature an article, research, your tech stack or list a job, hit me up! I would love to include it in my next edition😎.